نتایج جستجو برای: genetic algorithm ga

تعداد نتایج: 1327948  

Journal: :the modares journal of electrical engineering 2007
reza key pour mahmood reza haghifam hossin seifi

this paper presents a framework for long term transmission expansion planning in competitive, electricity markets. transmission lines and phase shifters are taken into account as expansion options. maximization of the network users' benefits, with satisfying security constraints are considered as the criterion for transmission expansion planning. the elements of the objective function are the...

تحسینی, حبیب اله, جهانی, میثم, رضایی نور, جلال, صالحی, ایرج, هداوندی, اسماعیل,

Background & Objectives: In recent years, different decision support systems (DSS) have been used to predict and diagnose diseases. The purpose of this paper was to compare some DSSs and to evaluate their accuracy in predicting diabetes.  Methods: In this research, determination and optimization of the weights of the neural network were undertaken using genetic algorithm and Levenberg-Marqua...

This paper presents a new mathematical model for integrated dynamic cellular manufacturing systems and production planning that minimizes machine purchasing, intra-cell material handling, cell reconfiguration and setup costs. The presented model forms the manufacturing cells and determines the quantity of machine and movements  during each period of time. This problem is NP-hard, so a meta-heur...

Journal: :نشریه دانشکده فنی 0
پرهام پهلوانی محمودرضا دلاور فرهاد صمدزادگان

multi-criteria shortest path problems (mspp) are called as np-hard. for mspps, a unique solution for optimizing all the criteria simultaneously will rarely exist in reality. algorithmic and approximation schemes are available to solve these problems; however, the complexity of these approaches often prohibits their implementation on real-world applications. this paper describes the development ...

Journal: :international journal of smart electrical engineering 0
alireza rezaee assistant professor of department of system and mechatronics engineering, faculty of new sciences and technologies, university of tehran,

brain-computer interface systems are a new mode of communication which provides a new path between brain and its surrounding by processing eeg signals measured in different mental states.  therefore, choosing suitable features is demanded for a good bci communication. in this regard, one of the points to be considered is feature vector dimensionality. we present a method of feature reduction us...

Journal: :journal of advances in computer engineering and technology 2015
vahid seydi ghomsheh mohamad teshnehlab mehdi aliyari shoordeli

this study proposes a modified version of cultural algorithms (cas) which benefits from rule-based system for influence function. this rule-based system selects and applies the suitable knowledge source according to the distribution of the solutions. this is important to use appropriate influence function to apply to a specific individual, regarding to its role in the search process. this rule ...

Abbasian, Mohammad , Nahavandi, Nasim ,

In this paper, Multi-Objective Flexible Job-Shop scheduling with Parallel Machines in Dynamic manufacturing environment (MO-FDJSPM) is investigated. Moreover considering dynamical job-shop environment (jobs arrived in non-zero time), It contains two kinds of flexibility which is effective for improving operational manufacturing systems. The non-flexibility leads to scheduling program which have...

Journal: :journal of electrical and computer engineering innovations 2013
m. h. refan a. dameshghi

if both reference station (rs) and navigational device in differential global positioning system (dgps) receive signals from the same satellite, rs position components error (rpce) can be used to compensate for navigational device error. this research used hybrid method for rpce prediction which was collected by a low-cost gps receiver. it is a combination of genetic algorithm (ga) computing an...

In this paper, the gain in LD-CELP speech coding algorithm is predicted using three neural models, that are equipped by genetic and particle swarm optimization (PSO) algorithms to optimize the structure and parameters of neural networks. Elman, multi-layer perceptron (MLP) and fuzzy ARTMAP are the candidate neural models. The optimized number of nodes in the first and second hidden layers of El...

Ali Nazemi Ashkan Hafezalkotob Seyed Hosein Mousavi

With the formation of the competitive electricity markets in the world, optimization of bidding strategies has become one of the main discussions in studies related to market designing. Market design is challenged by multiple objectives that need to be satisfied. The solution of those multi-objective problems is searched often over the combined strategy space, and thus requires the simultaneous...

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